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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/124936


    Title: 以深度學習模型預測台灣ETF價格走勢
    Authors: 吳凱華
    Wu, Kai-Hua
    Contributors: 蔡炎龍
    蕭明福

    吳凱華
    Wu, Kai-Hua
    Keywords: 深度學習
    類神經網路
    交易所買賣基金
    Date: 2019
    Issue Date: 2019-08-07 16:48:30 (UTC+8)
    Abstract: 交易所買賣基金(Exchange Traded Funds, ETF)有別於個股投資,具有分散風險的特性,是一種追蹤特定股價指數的投資商品,也就是一種將股票指數商品化並長期持有的金融商品。
    持有金融商品的目的就是獲利,因此價格或趨勢的預測準確率就變得相當的重要。文獻上實證發現類神經網路較傳統時間序列方法的預測能力高,加上近年機器學習快速發展,本文以類神經網路長短期記憶模型與生成對抗網路為研究方法,建立一個能廣泛運用在台灣非金融類交易所買賣基金的價格與走勢預測。變數除了有收盤價與成交量之外,交易所買賣基金屬於長期持有的商品,產業與總體的變化也是影響行情走勢的重要因素,因此加入匯豐台灣製造業採購經理人指數做為總體變數。此外,為了捕捉總體變數造成的價格影響,加入二十日與四十五日的收盤價移動平均捕捉價格趨勢。
    實證結果發現,使用長短期記憶模型具有預測波動較大的台灣非金融類交易所買賣基金之收盤價格能力,而生成對抗網路具有較高的預測漲跌能力,且行情確實為牛市的時候,生成對抗網路也有較高的能力夠捕捉此趨勢。
    Reference: 中文文獻
    胡依淳(2018),「深度卷積神經網路中卷積層之分析及比較」,國立暨南國際大學電機工程學系碩士論文。

    陳全溢(2018),「結合類神經網路預測與投資策略於台灣50指數股票型基金之操作」,國立中興大學資訊管理學系碩士論文。

    陳俊諺(2018),「運用類神經網路與田口法預測台灣ETF指數」,中原大學,資訊管理系碩士論文。

    黃焜烽(2018),「利用深度類神經網路模型預測台灣股價指數走勢」,國立臺北大學經濟系碩士論文。

    楊國良(2017),「運用倒傳遞類神經網路預測台灣50指數ETF股價走勢」,國立金門大學理工學院工程科技碩士在職專班資訊系統組碩士論文。

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    Description: 碩士
    國立政治大學
    經濟學系
    106258009
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106258009
    Data Type: thesis
    DOI: 10.6814/NCCU201900589
    Appears in Collections:[經濟學系] 學位論文

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